Abstract
The aim of this study was to improve the accuracy of aeropalynological models to forecast yields in areas with heterogeneous characteristics by applying principal component analysis to integrate the airborne pollen sampled from more than one trap. The sampling was performed during the past seven years (1998-2004) in the main northeast olive regions of Portugal. Annual crop production was forecasted on the basis of airborne pollen concentration measured at flowering, comparing the performance of three different independent variables: total airborne pollen concentration sampled in each trap and a derived variable that was determined by principal component analysis of the total airborne pollen concentration sampled. The best predictive results were obtained using a logarithmic relationship with airborne pollen concentration principal component scores describing about 97% of olive fruit production variability over the last seven years. The use of this technique improved the ability of pollen to explain the production interannual variations by about 13%. The comparison between actual reported and the adjusted production showed an average spread deviation of 5%.

Abstract
This paper proposes a method to unify the definition of the main pollen season based on statistical analysis. For this, an aerobiological study was carried out in Porto region (Portugal), from 2003-2005 using a 7-day Hirst-type volumetric spore trap. To define the main pollen season, a non-linear logistic regression model was fitted to the values of the accumulated sum of the daily airborne pollen concentration from several allergological species. An important feature of this method,is that the main pollen season will be characterized by the model parameters calculated. These parameters are identifiable aspects of the flowering phenology, and determine not only the beginning and end of the main pollen season, but are also influenced by the meteorological conditions. The results obtained with the proposed methodology were also compared with two of the most used percentage methods. The logistic model fitted well with the sum of accumulated pollen. The explained variance was always higher than 97%, and the exponential part of the predicted curve was well adjusted to the time when higher atmospheric pollen concentration was sampled. The comparison between the different methods tested showed large divergence in the duration and end dates of the main pollen season of the studied species.

Abstract

Abstract
In this paper, we propose an algorithm that combine the restriction on motor's velocities and the kinematic model of Omni-Directional mobile robots to improve the trajectory's following. The algorithm verifies the reference velocities of the robot and redefine them if necessary, in order to prevent possible saturation on motor's velocities. Simulation results of the algorithm applied to an omnidirectional mobile robot are presented. Copyright © 2006 IFAC.

Abstract
This paper presents the experimental identification of the model's parameters of an omni-directional mobile robot with four wheels. The parameters related to dynamic equations are the viscous frictions, the coulomb frictions and the inertia moment of the robot. Two methods of parameters identification are described. A simulation environment and simulation results are presented. Copyright © 2006 IFAC.

Abstract
This paper presents a new architecture for coordinating multiple autonomous robots in the execution of cooperative tasks. The architecture is based on the definition of a strategy that uses different tactics, setplays and roles. Roles enable to configure individual behaviour by performing specific tasks using a given set of actions. The proposed architecture allows flexible and efficient multi-robot operation in dynamic environments. The paper also presents an application of the proposed architecture to a complex domain such as middle-size robotic soccer. Our architecture is also generally enough to be applied in different robotic soccer leagues and similar multi-robot problems. Copyright © 2006 IFAC.